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Nuclear Criticality Safety
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Nuclear Science and Engineering
Fusion Science and Technology
Matthew Denman: On Probabilistic Risk Assessment
Probabilistic risk assessment is a systematic methodology for evaluating risks associated with a complex engineered technology such as nuclear energy. PRA risk is defined in terms of possible detrimental outcomes of an activity or action, and as such, risk is characterized by three quantities: what can go wrong, the likelihood of the problem, and the resulting consequences of the problem.
Matthew Denman is principal engineer for reliability engineering at Kairos Power and the chair of the American Nuclear Society and American Society of Mechanical Engineers Joint Committee on Nuclear Risk Management’s Subcommittee of Standards Development. As a college student at the University of Florida, Denman took a course on PRA but didn’t enjoy it, because he did not see its connection to the nuclear power industry. Later, during his Ph.D. study at the Massachusetts Institute of Technology, his advisor was Neil Todreas, a well-known thermal hydraulics expert. Todreas was working on a project with George Apostolakis, who would leave MIT to become a commissioner of the Nuclear Regulatory Commission. The project, “Risk Informing the Design of the Sodium-Cooled Fast Reactor,” was a multi-university effort funded through a Department of Energy Nuclear Energy Research Initiative (NERI) grant. Todreas and Apostolakis were joined in this project by a who’s who of nuclear academia, including Andy Kadak (MIT, ANS past president [1999–2000]), Mike Driscoll (MIT), Mike Golay (MIT), Mike Lineberry (Idaho State University, former ANS treasurer), Rich Denning (Ohio State University), and Tunc Aldemir (Ohio State University).
Andrea Murari, Guido Vagliasindi, Sebastiano De Fiore, Eleonora Arena, Paolo Arena, Luigi Fortuna, Y. Andrew, M. Johnson, JET-EFDA Contributors
Fusion Science and Technology | Volume 58 | Number 2 | October 2010 | Pages 695-705
Selected Paper from the Sixth Fusion Data Validation Workshop 2010 (Part 1) | dx.doi.org/10.13182/FST10-A10894
Articles are hosted by Taylor and Francis Online.
Dynamical systems are often considered immune from memory effects, i.e., the dependence of their time evolution on the previous history. This assumption has been tested for two phenomena in nuclear fusion that are believed to sometimes show sensitivity to the previous history of the discharge: disruptions and the transition from the L mode to the H mode of confinement. To this end, two neural network architectures, tapped delay lines and recurrent networks of the Elman type, have been applied to the Joint European Torus (JET) database to extract these potential memory effects from the time series of the available signals. Both architectures can detect the dependence on the previous evolution quite effectively. In the case of disruptions, only the ones triggered by locked modes seem to be influenced by the previous history of the discharge. With regard to the L-H transition, memory effects are present only in the time interval very close to the transition, whereas once the plasma has settled down in one of the two regimes, no evidence of dependence on the previous evolution has been detected.